Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

An N-Server Stochastic Service System with Customer Preferences

P. Lawrence Bein
Operations Research
Vol. 24, No. 1 (Jan. - Feb., 1976), pp. 104-117
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/169457
Page Count: 14
  • Download ($30.00)
  • Cite this Item
An N-Server Stochastic Service System with Customer Preferences
Preview not available

Abstract

The Erlang loss formula is currently used to estimate the capacity of a set of N linear curb spaces for vehicle parking; but this model applies only if drivers will accept the first vacant space they come to, a condition not found in practice. This paper develops a model of service that permits customers to decline an available server (space) when the walking distance would be excessive. The results enable the calculation of not only the overall loss, but the ability of the service system to satisfy customer preferences. It evaluates the conditional loss (given the space preferred), the access time, and the expected walking distance for each preference class. We give some examples of results based upon traffic characteristics forecast at a large, modern air terminal. It is found that the Erlang formula considerably underestimates the space requirements for linear curb parking and ignores the impact of its driver-indifference assumption upon passenger walking distance. The model has been programmed in APL for rapid calculations of all pertinent factors, allowing economical interactive use for planning-a curb with 30 spaces can be evaluated in approximately 1/2 second of CPU time.

Page Thumbnails

  • Thumbnail: Page 
104
    104
  • Thumbnail: Page 
105
    105
  • Thumbnail: Page 
106
    106
  • Thumbnail: Page 
107
    107
  • Thumbnail: Page 
108
    108
  • Thumbnail: Page 
109
    109
  • Thumbnail: Page 
110
    110
  • Thumbnail: Page 
111
    111
  • Thumbnail: Page 
112
    112
  • Thumbnail: Page 
113
    113
  • Thumbnail: Page 
114
    114
  • Thumbnail: Page 
115
    115
  • Thumbnail: Page 
116
    116
  • Thumbnail: Page 
117
    117